Overview

Dataset statistics

Number of variables25
Number of observations625
Missing cells3757
Missing cells (%)24.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory122.2 KiB
Average record size in memory200.2 B

Variable types

Numeric8
Categorical15
Unsupported2

Alerts

ended has a high cardinality: 105 distinct values High cardinality
genres has a high cardinality: 159 distinct values High cardinality
links_previousepisode_href has a high cardinality: 625 distinct values High cardinality
links_self_href has a high cardinality: 625 distinct values High cardinality
name has a high cardinality: 623 distinct values High cardinality
officialSite has a high cardinality: 567 distinct values High cardinality
premiered has a high cardinality: 399 distinct values High cardinality
summary has a high cardinality: 549 distinct values High cardinality
url has a high cardinality: 625 distinct values High cardinality
runtime is highly correlated with averageRuntimeHigh correlation
averageRuntime is highly correlated with runtimeHigh correlation
runtime is highly correlated with averageRuntimeHigh correlation
averageRuntime is highly correlated with runtimeHigh correlation
runtime is highly correlated with averageRuntimeHigh correlation
averageRuntime is highly correlated with runtimeHigh correlation
schedule_time is highly correlated with links_nextepisode_hrefHigh correlation
schedule_days is highly correlated with links_nextepisode_hrefHigh correlation
links_nextepisode_href is highly correlated with schedule_time and 4 other fieldsHigh correlation
status is highly correlated with links_nextepisode_hrefHigh correlation
type is highly correlated with links_nextepisode_hrefHigh correlation
language is highly correlated with links_nextepisode_hrefHigh correlation
show_id is highly correlated with weight and 2 other fieldsHigh correlation
type is highly correlated with status and 4 other fieldsHigh correlation
language is highly correlated with status and 4 other fieldsHigh correlation
status is highly correlated with type and 3 other fieldsHigh correlation
runtime is highly correlated with type and 3 other fieldsHigh correlation
averageRuntime is highly correlated with type and 2 other fieldsHigh correlation
schedule_time is highly correlated with type and 3 other fieldsHigh correlation
schedule_days is highly correlated with links_nextepisode_href and 1 other fieldsHigh correlation
rating_average is highly correlated with links_nextepisode_hrefHigh correlation
weight is highly correlated with show_id and 1 other fieldsHigh correlation
updated is highly correlated with links_nextepisode_hrefHigh correlation
links_nextepisode_href is highly correlated with show_id and 11 other fieldsHigh correlation
webChannel_id is highly correlated with language and 2 other fieldsHigh correlation
network_id is highly correlated with show_id and 4 other fieldsHigh correlation
averageRuntime has 32 (5.1%) missing values Missing
ended has 406 (65.0%) missing values Missing
image has 625 (100.0%) missing values Missing
language has 8 (1.3%) missing values Missing
links_nextepisode_href has 593 (94.9%) missing values Missing
network has 625 (100.0%) missing values Missing
network_id has 573 (91.7%) missing values Missing
officialSite has 58 (9.3%) missing values Missing
rating_average has 530 (84.8%) missing values Missing
runtime has 214 (34.2%) missing values Missing
summary has 76 (12.2%) missing values Missing
webChannel_id has 17 (2.7%) missing values Missing
links_nextepisode_href is uniformly distributed Uniform
links_previousepisode_href is uniformly distributed Uniform
links_self_href is uniformly distributed Uniform
name is uniformly distributed Uniform
officialSite is uniformly distributed Uniform
summary is uniformly distributed Uniform
url is uniformly distributed Uniform
links_previousepisode_href has unique values Unique
links_self_href has unique values Unique
show_id has unique values Unique
updated has unique values Unique
url has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
network is an unsupported type, check if it needs cleaning or further analysis Unsupported
weight has 7 (1.1%) zeros Zeros

Reproduction

Analysis started2022-08-01 02:19:42.938504
Analysis finished2022-08-01 02:19:49.106121
Duration6.17 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct89
Distinct (%)15.0%
Missing32
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean36.04890388
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:49.172013image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q116
median29
Q346
95-th percentile90
Maximum300
Range299
Interquartile range (IQR)30

Descriptive statistics

Standard deviation31.11659584
Coefficient of variation (CV)0.863177309
Kurtosis15.10927654
Mean36.04890388
Median Absolute Deviation (MAD)16
Skewness3.034746571
Sum21377
Variance968.2425368
MonotonicityNot monotonic
2022-07-31T21:19:49.253031image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3040
 
6.4%
4539
 
6.2%
6033
 
5.3%
2527
 
4.3%
2021
 
3.4%
1520
 
3.2%
5018
 
2.9%
1017
 
2.7%
516
 
2.6%
1215
 
2.4%
Other values (79)347
55.5%
(Missing)32
 
5.1%
ValueCountFrequency (%)
12
 
0.3%
25
 
0.8%
35
 
0.8%
44
 
0.6%
516
2.6%
66
 
1.0%
78
1.3%
87
1.1%
95
 
0.8%
1017
2.7%
ValueCountFrequency (%)
3001
0.2%
2111
0.2%
1951
0.2%
1931
0.2%
1881
0.2%
1811
0.2%
1802
0.3%
1351
0.2%
1301
0.2%
1291
0.2%

ended
Categorical

HIGH CARDINALITY
MISSING

Distinct105
Distinct (%)47.9%
Missing406
Missing (%)65.0%
Memory size5.0 KiB
2020-12-18
 
10
2020-12-10
 
9
2020-12-11
 
7
2020-12-16
 
7
2020-12-22
 
5
Other values (100)
181 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2190
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)28.3%

Sample

1st row2020-12-11
2nd row2020-12-22
3rd row2020-12-08
4th row2020-12-01
5th row2020-12-24

Common Values

ValueCountFrequency (%)
2020-12-1810
 
1.6%
2020-12-109
 
1.4%
2020-12-117
 
1.1%
2020-12-167
 
1.1%
2020-12-225
 
0.8%
2020-12-245
 
0.8%
2020-12-285
 
0.8%
2020-12-135
 
0.8%
2020-12-255
 
0.8%
2020-12-145
 
0.8%
Other values (95)156
 
25.0%
(Missing)406
65.0%

Length

2022-07-31T21:19:49.317742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-1810
 
4.6%
2020-12-109
 
4.1%
2020-12-117
 
3.2%
2020-12-167
 
3.2%
2020-12-225
 
2.3%
2020-12-245
 
2.3%
2020-12-285
 
2.3%
2020-12-135
 
2.3%
2020-12-255
 
2.3%
2020-12-145
 
2.3%
Other values (95)156
71.2%

Most occurring characters

ValueCountFrequency (%)
2673
30.7%
0521
23.8%
-438
20.0%
1373
17.0%
339
 
1.8%
830
 
1.4%
625
 
1.1%
525
 
1.1%
723
 
1.1%
922
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1752
80.0%
Dash Punctuation438
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2673
38.4%
0521
29.7%
1373
21.3%
339
 
2.2%
830
 
1.7%
625
 
1.4%
525
 
1.4%
723
 
1.3%
922
 
1.3%
421
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
-438
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2673
30.7%
0521
23.8%
-438
20.0%
1373
17.0%
339
 
1.8%
830
 
1.4%
625
 
1.1%
525
 
1.1%
723
 
1.1%
922
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2673
30.7%
0521
23.8%
-438
20.0%
1373
17.0%
339
 
1.8%
830
 
1.4%
625
 
1.1%
525
 
1.1%
723
 
1.1%
922
 
1.0%

genres
Categorical

HIGH CARDINALITY

Distinct159
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
[]
173 
['Comedy']
74 
['Drama', 'Romance']
41 
['Drama']
 
19
['Drama', 'Comedy', 'Romance']
 
15
Other values (154)
303 

Length

Max length51
Median length45
Mean length15.6528
Min length2

Characters and Unicode

Total characters9783
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)16.3%

Sample

1st row[]
2nd row['Comedy']
3rd row['Music']
4th row['Action', 'Anime', 'Science-Fiction']
5th row['Action', 'Adventure', 'Anime', 'Fantasy']

Common Values

ValueCountFrequency (%)
[]173
27.7%
['Comedy']74
 
11.8%
['Drama', 'Romance']41
 
6.6%
['Drama']19
 
3.0%
['Drama', 'Comedy', 'Romance']15
 
2.4%
['Sports']15
 
2.4%
['Drama', 'Comedy']13
 
2.1%
['Comedy', 'Children']10
 
1.6%
['Crime']9
 
1.4%
['Food']9
 
1.4%
Other values (149)247
39.5%

Length

2022-07-31T21:19:49.384159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
comedy180
16.7%
173
16.0%
drama169
15.7%
romance89
 
8.2%
children40
 
3.7%
crime40
 
3.7%
action38
 
3.5%
adventure35
 
3.2%
fantasy35
 
3.2%
mystery31
 
2.9%
Other values (17)249
23.1%

Most occurring characters

ValueCountFrequency (%)
'1812
18.5%
[625
 
6.4%
]625
 
6.4%
e587
 
6.0%
a578
 
5.9%
m533
 
5.4%
r506
 
5.2%
,454
 
4.6%
454
 
4.6%
o437
 
4.5%
Other values (28)3172
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4859
49.7%
Other Punctuation2266
23.2%
Uppercase Letter932
 
9.5%
Open Punctuation625
 
6.4%
Close Punctuation625
 
6.4%
Space Separator454
 
4.6%
Dash Punctuation22
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e587
12.1%
a578
11.9%
m533
11.0%
r506
10.4%
o437
9.0%
n326
6.7%
y321
6.6%
i316
6.5%
d279
 
5.7%
c223
 
4.6%
Other values (8)753
15.5%
Uppercase Letter
ValueCountFrequency (%)
C260
27.9%
D171
18.3%
A104
 
11.2%
F101
 
10.8%
R89
 
9.5%
M61
 
6.5%
S58
 
6.2%
T36
 
3.9%
H34
 
3.6%
W6
 
0.6%
Other values (4)12
 
1.3%
Other Punctuation
ValueCountFrequency (%)
'1812
80.0%
,454
 
20.0%
Open Punctuation
ValueCountFrequency (%)
[625
100.0%
Close Punctuation
ValueCountFrequency (%)
]625
100.0%
Space Separator
ValueCountFrequency (%)
454
100.0%
Dash Punctuation
ValueCountFrequency (%)
-22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5791
59.2%
Common3992
40.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e587
 
10.1%
a578
 
10.0%
m533
 
9.2%
r506
 
8.7%
o437
 
7.5%
n326
 
5.6%
y321
 
5.5%
i316
 
5.5%
d279
 
4.8%
C260
 
4.5%
Other values (22)1648
28.5%
Common
ValueCountFrequency (%)
'1812
45.4%
[625
 
15.7%
]625
 
15.7%
,454
 
11.4%
454
 
11.4%
-22
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII9783
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'1812
18.5%
[625
 
6.4%
]625
 
6.4%
e587
 
6.0%
a578
 
5.9%
m533
 
5.4%
r506
 
5.2%
,454
 
4.6%
454
 
4.6%
o437
 
4.5%
Other values (28)3172
32.4%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing625
Missing (%)100.0%
Memory size5.0 KiB

language
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct36
Distinct (%)5.8%
Missing8
Missing (%)1.3%
Memory size5.0 KiB
English
239 
Russian
66 
Chinese
65 
Norwegian
45 
Korean
33 
Other values (31)
169 

Length

Max length10
Median length7
Mean length6.983792545
Min length4

Characters and Unicode

Total characters4309
Distinct characters43
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)1.8%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
English239
38.2%
Russian66
 
10.6%
Chinese65
 
10.4%
Norwegian45
 
7.2%
Korean33
 
5.3%
Thai19
 
3.0%
Japanese15
 
2.4%
German13
 
2.1%
Spanish13
 
2.1%
Tagalog13
 
2.1%
Other values (26)96
15.4%

Length

2022-07-31T21:19:49.453585image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english239
38.7%
russian66
 
10.7%
chinese65
 
10.5%
norwegian45
 
7.3%
korean33
 
5.3%
thai19
 
3.1%
japanese15
 
2.4%
german13
 
2.1%
spanish13
 
2.1%
tagalog13
 
2.1%
Other values (26)96
15.6%

Most occurring characters

ValueCountFrequency (%)
n541
12.6%
i529
12.3%
s503
11.7%
h382
8.9%
g322
7.5%
e303
 
7.0%
a299
 
6.9%
l263
 
6.1%
E239
 
5.5%
r136
 
3.2%
Other values (33)792
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3692
85.7%
Uppercase Letter617
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n541
14.7%
i529
14.3%
s503
13.6%
h382
10.3%
g322
8.7%
e303
8.2%
a299
8.1%
l263
7.1%
r136
 
3.7%
o104
 
2.8%
Other values (13)310
8.4%
Uppercase Letter
ValueCountFrequency (%)
E239
38.7%
R67
 
10.9%
C65
 
10.5%
N45
 
7.3%
T43
 
7.0%
K34
 
5.5%
S23
 
3.7%
J15
 
2.4%
G14
 
2.3%
P13
 
2.1%
Other values (10)59
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
Latin4309
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n541
12.6%
i529
12.3%
s503
11.7%
h382
8.9%
g322
7.5%
e303
 
7.0%
a299
 
6.9%
l263
 
6.1%
E239
 
5.5%
r136
 
3.2%
Other values (33)792
18.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII4309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n541
12.6%
i529
12.3%
s503
11.7%
h382
8.9%
g322
7.5%
e303
 
7.0%
a299
 
6.9%
l263
 
6.1%
E239
 
5.5%
r136
 
3.2%
Other values (33)792
18.4%

links_nextepisode_href
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct32
Distinct (%)100.0%
Missing593
Missing (%)94.9%
Memory size5.0 KiB
https://api.tvmaze.com/episodes/2330389
 
1
https://api.tvmaze.com/episodes/2164180
 
1
https://api.tvmaze.com/episodes/2367426
 
1
https://api.tvmaze.com/episodes/2332522
 
1
https://api.tvmaze.com/episodes/2364562
 
1
Other values (27)
27 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters1248
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2309432
2nd rowhttps://api.tvmaze.com/episodes/2367080
3rd rowhttps://api.tvmaze.com/episodes/2366074
4th rowhttps://api.tvmaze.com/episodes/2357116
5th rowhttps://api.tvmaze.com/episodes/2359049

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23303891
 
0.2%
https://api.tvmaze.com/episodes/21641801
 
0.2%
https://api.tvmaze.com/episodes/23674261
 
0.2%
https://api.tvmaze.com/episodes/23325221
 
0.2%
https://api.tvmaze.com/episodes/23645621
 
0.2%
https://api.tvmaze.com/episodes/23286471
 
0.2%
https://api.tvmaze.com/episodes/23263981
 
0.2%
https://api.tvmaze.com/episodes/23509101
 
0.2%
https://api.tvmaze.com/episodes/23301801
 
0.2%
https://api.tvmaze.com/episodes/23683681
 
0.2%
Other values (22)22
 
3.5%
(Missing)593
94.9%

Length

2022-07-31T21:19:49.512448image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23303891
 
3.1%
https://api.tvmaze.com/episodes/21641801
 
3.1%
https://api.tvmaze.com/episodes/23670801
 
3.1%
https://api.tvmaze.com/episodes/23660741
 
3.1%
https://api.tvmaze.com/episodes/23571161
 
3.1%
https://api.tvmaze.com/episodes/23590491
 
3.1%
https://api.tvmaze.com/episodes/23667201
 
3.1%
https://api.tvmaze.com/episodes/23671021
 
3.1%
https://api.tvmaze.com/episodes/23462711
 
3.1%
https://api.tvmaze.com/episodes/23577121
 
3.1%
Other values (22)22
68.8%

Most occurring characters

ValueCountFrequency (%)
/128
 
10.3%
p96
 
7.7%
s96
 
7.7%
e96
 
7.7%
t96
 
7.7%
o64
 
5.1%
a64
 
5.1%
i64
 
5.1%
.64
 
5.1%
m64
 
5.1%
Other values (16)416
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter800
64.1%
Other Punctuation224
 
17.9%
Decimal Number224
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p96
12.0%
s96
12.0%
e96
12.0%
t96
12.0%
o64
8.0%
a64
8.0%
i64
8.0%
m64
8.0%
h32
 
4.0%
d32
 
4.0%
Other values (3)96
12.0%
Decimal Number
ValueCountFrequency (%)
252
23.2%
341
18.3%
629
12.9%
521
9.4%
017
 
7.6%
817
 
7.6%
714
 
6.2%
413
 
5.8%
112
 
5.4%
98
 
3.6%
Other Punctuation
ValueCountFrequency (%)
/128
57.1%
.64
28.6%
:32
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin800
64.1%
Common448
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/128
28.6%
.64
14.3%
252
11.6%
341
 
9.2%
:32
 
7.1%
629
 
6.5%
521
 
4.7%
017
 
3.8%
817
 
3.8%
714
 
3.1%
Other values (3)33
 
7.4%
Latin
ValueCountFrequency (%)
p96
12.0%
s96
12.0%
e96
12.0%
t96
12.0%
o64
8.0%
a64
8.0%
i64
8.0%
m64
8.0%
h32
 
4.0%
d32
 
4.0%
Other values (3)96
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/128
 
10.3%
p96
 
7.7%
s96
 
7.7%
e96
 
7.7%
t96
 
7.7%
o64
 
5.1%
a64
 
5.1%
i64
 
5.1%
.64
 
5.1%
m64
 
5.1%
Other values (16)416
33.3%

links_previousepisode_href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
https://api.tvmaze.com/episodes/1988862
 
1
https://api.tvmaze.com/episodes/2238897
 
1
https://api.tvmaze.com/episodes/2074193
 
1
https://api.tvmaze.com/episodes/2366086
 
1
https://api.tvmaze.com/episodes/2092041
 
1
Other values (620)
620 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters24375
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique625 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/1986873
3rd rowhttps://api.tvmaze.com/episodes/2245512
4th rowhttps://api.tvmaze.com/episodes/1964569
5th rowhttps://api.tvmaze.com/episodes/2309431

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888621
 
0.2%
https://api.tvmaze.com/episodes/22388971
 
0.2%
https://api.tvmaze.com/episodes/20741931
 
0.2%
https://api.tvmaze.com/episodes/23660861
 
0.2%
https://api.tvmaze.com/episodes/20920411
 
0.2%
https://api.tvmaze.com/episodes/23525911
 
0.2%
https://api.tvmaze.com/episodes/23004461
 
0.2%
https://api.tvmaze.com/episodes/20457881
 
0.2%
https://api.tvmaze.com/episodes/23250951
 
0.2%
https://api.tvmaze.com/episodes/23571291
 
0.2%
Other values (615)615
98.4%

Length

2022-07-31T21:19:49.567701image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888621
 
0.2%
https://api.tvmaze.com/episodes/23367551
 
0.2%
https://api.tvmaze.com/episodes/23099401
 
0.2%
https://api.tvmaze.com/episodes/22455121
 
0.2%
https://api.tvmaze.com/episodes/19645691
 
0.2%
https://api.tvmaze.com/episodes/23094311
 
0.2%
https://api.tvmaze.com/episodes/23151171
 
0.2%
https://api.tvmaze.com/episodes/19735451
 
0.2%
https://api.tvmaze.com/episodes/19842641
 
0.2%
https://api.tvmaze.com/episodes/22990871
 
0.2%
Other values (615)615
98.4%

Most occurring characters

ValueCountFrequency (%)
/2500
 
10.3%
t1875
 
7.7%
p1875
 
7.7%
s1875
 
7.7%
e1875
 
7.7%
a1250
 
5.1%
i1250
 
5.1%
.1250
 
5.1%
m1250
 
5.1%
o1250
 
5.1%
Other values (16)8125
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15625
64.1%
Other Punctuation4375
 
17.9%
Decimal Number4375
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t1875
12.0%
p1875
12.0%
s1875
12.0%
e1875
12.0%
a1250
8.0%
i1250
8.0%
m1250
8.0%
o1250
8.0%
h625
 
4.0%
d625
 
4.0%
Other values (3)1875
12.0%
Decimal Number
ValueCountFrequency (%)
2831
19.0%
1532
12.2%
9520
11.9%
3439
10.0%
0396
9.1%
7355
8.1%
8332
 
7.6%
6327
 
7.5%
5326
 
7.5%
4317
 
7.2%
Other Punctuation
ValueCountFrequency (%)
/2500
57.1%
.1250
28.6%
:625
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin15625
64.1%
Common8750
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/2500
28.6%
.1250
14.3%
2831
 
9.5%
:625
 
7.1%
1532
 
6.1%
9520
 
5.9%
3439
 
5.0%
0396
 
4.5%
7355
 
4.1%
8332
 
3.8%
Other values (3)970
 
11.1%
Latin
ValueCountFrequency (%)
t1875
12.0%
p1875
12.0%
s1875
12.0%
e1875
12.0%
a1250
8.0%
i1250
8.0%
m1250
8.0%
o1250
8.0%
h625
 
4.0%
d625
 
4.0%
Other values (3)1875
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII24375
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/2500
 
10.3%
t1875
 
7.7%
p1875
 
7.7%
s1875
 
7.7%
e1875
 
7.7%
a1250
 
5.1%
i1250
 
5.1%
.1250
 
5.1%
m1250
 
5.1%
o1250
 
5.1%
Other values (16)8125
33.3%

links_self_href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
https://api.tvmaze.com/shows/41648
 
1
https://api.tvmaze.com/shows/49484
 
1
https://api.tvmaze.com/shows/54837
 
1
https://api.tvmaze.com/shows/62306
 
1
https://api.tvmaze.com/shows/23401
 
1
Other values (620)
620 

Length

Max length34
Median length34
Mean length33.9632
Min length32

Characters and Unicode

Total characters21227
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique625 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/52198
3rd rowhttps://api.tvmaze.com/shows/52933
4th rowhttps://api.tvmaze.com/shows/51336
5th rowhttps://api.tvmaze.com/shows/54033

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/416481
 
0.2%
https://api.tvmaze.com/shows/494841
 
0.2%
https://api.tvmaze.com/shows/548371
 
0.2%
https://api.tvmaze.com/shows/623061
 
0.2%
https://api.tvmaze.com/shows/234011
 
0.2%
https://api.tvmaze.com/shows/497211
 
0.2%
https://api.tvmaze.com/shows/604271
 
0.2%
https://api.tvmaze.com/shows/411921
 
0.2%
https://api.tvmaze.com/shows/438831
 
0.2%
https://api.tvmaze.com/shows/450901
 
0.2%
Other values (615)615
98.4%

Length

2022-07-31T21:19:49.628175image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/416481
 
0.2%
https://api.tvmaze.com/shows/550161
 
0.2%
https://api.tvmaze.com/shows/529841
 
0.2%
https://api.tvmaze.com/shows/529331
 
0.2%
https://api.tvmaze.com/shows/513361
 
0.2%
https://api.tvmaze.com/shows/540331
 
0.2%
https://api.tvmaze.com/shows/616741
 
0.2%
https://api.tvmaze.com/shows/520381
 
0.2%
https://api.tvmaze.com/shows/523731
 
0.2%
https://api.tvmaze.com/shows/573391
 
0.2%
Other values (615)615
98.4%

Most occurring characters

ValueCountFrequency (%)
/2500
 
11.8%
s1875
 
8.8%
t1875
 
8.8%
h1250
 
5.9%
p1250
 
5.9%
a1250
 
5.9%
o1250
 
5.9%
.1250
 
5.9%
m1250
 
5.9%
e625
 
2.9%
Other values (16)6852
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter13750
64.8%
Other Punctuation4375
 
20.6%
Decimal Number3102
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s1875
13.6%
t1875
13.6%
h1250
9.1%
p1250
9.1%
a1250
9.1%
o1250
9.1%
m1250
9.1%
e625
 
4.5%
w625
 
4.5%
c625
 
4.5%
Other values (3)1875
13.6%
Decimal Number
ValueCountFrequency (%)
5540
17.4%
4400
12.9%
1330
10.6%
2322
10.4%
3301
9.7%
6261
8.4%
9250
8.1%
0248
8.0%
8240
7.7%
7210
 
6.8%
Other Punctuation
ValueCountFrequency (%)
/2500
57.1%
.1250
28.6%
:625
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin13750
64.8%
Common7477
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/2500
33.4%
.1250
16.7%
:625
 
8.4%
5540
 
7.2%
4400
 
5.3%
1330
 
4.4%
2322
 
4.3%
3301
 
4.0%
6261
 
3.5%
9250
 
3.3%
Other values (3)698
 
9.3%
Latin
ValueCountFrequency (%)
s1875
13.6%
t1875
13.6%
h1250
9.1%
p1250
9.1%
a1250
9.1%
o1250
9.1%
m1250
9.1%
e625
 
4.5%
w625
 
4.5%
c625
 
4.5%
Other values (3)1875
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII21227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/2500
 
11.8%
s1875
 
8.8%
t1875
 
8.8%
h1250
 
5.9%
p1250
 
5.9%
a1250
 
5.9%
o1250
 
5.9%
.1250
 
5.9%
m1250
 
5.9%
e625
 
2.9%
Other values (16)6852
32.3%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct623
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Mermaid Prince
 
2
Klassen
 
2
Bare Knuckle Fighting Championship
 
1
My Lecturer, My Husband
 
1
Rainbow High
 
1
Other values (618)
618 

Length

Max length51
Median length36
Mean length16.544
Min length3

Characters and Unicode

Total characters10340
Distinct characters172
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique621 ?
Unique (%)99.4%

Sample

1st rowSim for You
2nd rowКотики
3rd rowLAB с Антоном Беляевым
4th rowCore Sense
5th rowWu Shen Zhu Zai

Common Values

ValueCountFrequency (%)
Mermaid Prince2
 
0.3%
Klassen2
 
0.3%
Bare Knuckle Fighting Championship1
 
0.2%
My Lecturer, My Husband1
 
0.2%
Rainbow High1
 
0.2%
Mickey Mouse: Mixed-Up Adventures1
 
0.2%
Madagascar: A Little Wild1
 
0.2%
Justimus esittää: Duo1
 
0.2%
Just Roll With It1
 
0.2%
The Amber Ruffin Show1
 
0.2%
Other values (613)613
98.1%

Length

2022-07-31T21:19:49.707582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the85
 
4.8%
of25
 
1.4%
a15
 
0.9%
love13
 
0.7%
with13
 
0.7%
you12
 
0.7%
in11
 
0.6%
my9
 
0.5%
wwe9
 
0.5%
i9
 
0.5%
Other values (1276)1555
88.6%

Most occurring characters

ValueCountFrequency (%)
1131
 
10.9%
e926
 
9.0%
a597
 
5.8%
o535
 
5.2%
i500
 
4.8%
r497
 
4.8%
n492
 
4.8%
t445
 
4.3%
s442
 
4.3%
l320
 
3.1%
Other values (162)4455
43.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7309
70.7%
Uppercase Letter1647
 
15.9%
Space Separator1131
 
10.9%
Other Punctuation161
 
1.6%
Decimal Number71
 
0.7%
Dash Punctuation16
 
0.2%
Close Punctuation2
 
< 0.1%
Currency Symbol2
 
< 0.1%
Open Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e926
12.7%
a597
 
8.2%
o535
 
7.3%
i500
 
6.8%
r497
 
6.8%
n492
 
6.7%
t445
 
6.1%
s442
 
6.0%
l320
 
4.4%
h281
 
3.8%
Other values (75)2274
31.1%
Uppercase Letter
ValueCountFrequency (%)
T162
 
9.8%
S133
 
8.1%
C103
 
6.3%
M101
 
6.1%
A88
 
5.3%
B88
 
5.3%
W79
 
4.8%
L77
 
4.7%
R76
 
4.6%
D74
 
4.5%
Other values (48)666
40.4%
Other Punctuation
ValueCountFrequency (%)
:49
30.4%
'41
25.5%
.26
16.1%
!14
 
8.7%
,9
 
5.6%
?8
 
5.0%
&6
 
3.7%
#2
 
1.2%
/2
 
1.2%
"2
 
1.2%
Other values (2)2
 
1.2%
Decimal Number
ValueCountFrequency (%)
022
31.0%
218
25.4%
19
12.7%
37
 
9.9%
75
 
7.0%
54
 
5.6%
42
 
2.8%
62
 
2.8%
81
 
1.4%
91
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
-15
93.8%
1
 
6.2%
Currency Symbol
ValueCountFrequency (%)
$1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1131
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8204
79.3%
Common1384
 
13.4%
Cyrillic731
 
7.1%
Greek21
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e926
 
11.3%
a597
 
7.3%
o535
 
6.5%
i500
 
6.1%
r497
 
6.1%
n492
 
6.0%
t445
 
5.4%
s442
 
5.4%
l320
 
3.9%
h281
 
3.4%
Other values (57)3169
38.6%
Cyrillic
ValueCountFrequency (%)
о72
 
9.8%
и53
 
7.3%
е50
 
6.8%
а48
 
6.6%
р41
 
5.6%
к39
 
5.3%
н38
 
5.2%
т38
 
5.2%
с34
 
4.7%
м22
 
3.0%
Other values (49)296
40.5%
Common
ValueCountFrequency (%)
1131
81.7%
:49
 
3.5%
'41
 
3.0%
.26
 
1.9%
022
 
1.6%
218
 
1.3%
-15
 
1.1%
!14
 
1.0%
19
 
0.7%
,9
 
0.7%
Other values (19)50
 
3.6%
Greek
ValueCountFrequency (%)
ς3
14.3%
έ2
 
9.5%
ε2
 
9.5%
Ψ1
 
4.8%
γ1
 
4.8%
Ε1
 
4.8%
χ1
 
4.8%
ο1
 
4.8%
ώ1
 
4.8%
ρ1
 
4.8%
Other values (7)7
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII9542
92.3%
Cyrillic731
 
7.1%
None65
 
0.6%
Currency Symbols1
 
< 0.1%
Punctuation1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1131
 
11.9%
e926
 
9.7%
a597
 
6.3%
o535
 
5.6%
i500
 
5.2%
r497
 
5.2%
n492
 
5.2%
t445
 
4.7%
s442
 
4.6%
l320
 
3.4%
Other values (69)3657
38.3%
Cyrillic
ValueCountFrequency (%)
о72
 
9.8%
и53
 
7.3%
е50
 
6.8%
а48
 
6.6%
р41
 
5.6%
к39
 
5.3%
н38
 
5.2%
т38
 
5.2%
с34
 
4.7%
м22
 
3.0%
Other values (49)296
40.5%
None
ValueCountFrequency (%)
ø9
 
13.8%
å6
 
9.2%
é6
 
9.2%
ä5
 
7.7%
á4
 
6.2%
ı3
 
4.6%
ς3
 
4.6%
í2
 
3.1%
έ2
 
3.1%
ε2
 
3.1%
Other values (22)23
35.4%
Currency Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing625
Missing (%)100.0%
Memory size5.0 KiB

network_id
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct42
Distinct (%)80.8%
Missing573
Missing (%)91.7%
Infinite0
Infinite (%)0.0%
Mean503.0769231
Minimum8
Maximum1862
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:49.784540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile33.85
Q185
median251
Q3607.25
95-th percentile1784.9
Maximum1862
Range1854
Interquartile range (IQR)522.25

Descriptive statistics

Standard deviation580.969266
Coefficient of variation (CV)1.154831874
Kurtosis0.2245803002
Mean503.0769231
Median Absolute Deviation (MAD)173
Skewness1.284788528
Sum26160
Variance337525.2881
MonotonicityNot monotonic
2022-07-31T21:19:49.852253image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
784
 
0.6%
3082
 
0.3%
18082
 
0.3%
852
 
0.3%
912
 
0.3%
1322
 
0.3%
302
 
0.3%
3742
 
0.3%
7551
 
0.2%
2361
 
0.2%
Other values (32)32
 
5.1%
(Missing)573
91.7%
ValueCountFrequency (%)
81
 
0.2%
302
0.3%
371
 
0.2%
411
 
0.2%
491
 
0.2%
511
 
0.2%
761
 
0.2%
784
0.6%
852
0.3%
912
0.3%
ValueCountFrequency (%)
18621
0.2%
18082
0.3%
17661
0.2%
16831
0.2%
15691
0.2%
13541
0.2%
13201
0.2%
12821
0.2%
12621
0.2%
10751
0.2%

officialSite
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct567
Distinct (%)100.0%
Missing58
Missing (%)9.3%
Memory size5.0 KiB
https://www.vlive.tv/video/121637
 
1
https://www.hulu.com/series/madagascar-a-little-wild-7a11e023-5762-4980-bfce-7f337e4c28ef
 
1
https://www.youtube.com/watch?v=GD9vpqOFDdg&list=PLXL6rKxsZjLItPoOykgmYhL1GLOQu3mEj&ab_channel=LeJimmyLabeeu
 
1
https://www.youtube.com/playlist?list=PLRXdsS5E_8i3FJ_o7VF0TFb9SUdWk54iW
 
1
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d
 
1
Other values (562)
562 

Length

Max length250
Median length88
Mean length50.82892416
Min length15

Characters and Unicode

Total characters28820
Distinct characters77
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique567 ?
Unique (%)100.0%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttp://epic-media.ru/project/kotiki
3rd rowhttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva
4th rowhttps://www.bilibili.com/bangumi/media/md28223064
5th rowhttps://v.qq.com/detail/m/7q544xyrava3vxf.html

Common Values

ValueCountFrequency (%)
https://www.vlive.tv/video/1216371
 
0.2%
https://www.hulu.com/series/madagascar-a-little-wild-7a11e023-5762-4980-bfce-7f337e4c28ef1
 
0.2%
https://www.youtube.com/watch?v=GD9vpqOFDdg&list=PLXL6rKxsZjLItPoOykgmYhL1GLOQu3mEj&ab_channel=LeJimmyLabeeu1
 
0.2%
https://www.youtube.com/playlist?list=PLRXdsS5E_8i3FJ_o7VF0TFb9SUdWk54iW1
 
0.2%
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d1
 
0.2%
https://wetv.vip/en/play/if9a67aohhr5cpj-My%20Lecturer%20My%20Husband?vid=l0034l08wvp1
 
0.2%
https://www.youtube.com/c/RainbowHigh1
 
0.2%
https://disneynow.com/shows/mickey-mouse-mixed-up-adventures1
 
0.2%
https://areena.yle.fi/1-502840411
 
0.2%
https://tv.line.me/taynewmealdate1
 
0.2%
Other values (557)557
89.1%
(Missing)58
 
9.3%

Length

2022-07-31T21:19:49.939747image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://tv.naver.com/whatwomenwant2
 
0.4%
https://www.vlive.tv/video/1216371
 
0.2%
https://www.youtube.com/playlist?list=plhknwtrzfo2g74twgelcoo2t3wwbn7aga1
 
0.2%
https://tv.nrk.no/serie/stjernestoev1
 
0.2%
https://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva1
 
0.2%
https://www.bilibili.com/bangumi/media/md282230641
 
0.2%
https://v.qq.com/detail/m/7q544xyrava3vxf.html1
 
0.2%
https://www.paravi.jp/static/koisuko1
 
0.2%
https://v.qq.com/x/cover/2w2legt0g8z26al.html1
 
0.2%
http://vmesteproject.ru/intervue1
 
0.2%
Other values (556)556
98.1%

Most occurring characters

ValueCountFrequency (%)
/2324
 
8.1%
t2255
 
7.8%
s1528
 
5.3%
e1516
 
5.3%
w1325
 
4.6%
o1296
 
4.5%
.1106
 
3.8%
h1054
 
3.7%
i1032
 
3.6%
p990
 
3.4%
Other values (67)14394
49.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19502
67.7%
Other Punctuation4337
 
15.0%
Decimal Number2343
 
8.1%
Uppercase Letter1863
 
6.5%
Dash Punctuation558
 
1.9%
Math Symbol130
 
0.5%
Connector Punctuation87
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t2255
 
11.6%
s1528
 
7.8%
e1516
 
7.8%
w1325
 
6.8%
o1296
 
6.6%
h1054
 
5.4%
i1032
 
5.3%
p990
 
5.1%
a961
 
4.9%
l840
 
4.3%
Other values (16)6705
34.4%
Uppercase Letter
ValueCountFrequency (%)
P127
 
6.8%
L122
 
6.5%
A115
 
6.2%
B108
 
5.8%
E107
 
5.7%
C103
 
5.5%
D88
 
4.7%
N70
 
3.8%
S69
 
3.7%
U69
 
3.7%
Other values (16)885
47.5%
Other Punctuation
ValueCountFrequency (%)
/2324
53.6%
.1106
25.5%
:612
 
14.1%
%171
 
3.9%
?86
 
2.0%
&29
 
0.7%
,3
 
0.1%
'2
 
< 0.1%
#2
 
< 0.1%
!2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0347
14.8%
1286
12.2%
8258
11.0%
2247
10.5%
4223
9.5%
9218
9.3%
3212
9.0%
6198
8.5%
7185
7.9%
5169
7.2%
Math Symbol
ValueCountFrequency (%)
=123
94.6%
~4
 
3.1%
+3
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
-558
100.0%
Connector Punctuation
ValueCountFrequency (%)
_87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin21365
74.1%
Common7455
 
25.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t2255
 
10.6%
s1528
 
7.2%
e1516
 
7.1%
w1325
 
6.2%
o1296
 
6.1%
h1054
 
4.9%
i1032
 
4.8%
p990
 
4.6%
a961
 
4.5%
l840
 
3.9%
Other values (42)8568
40.1%
Common
ValueCountFrequency (%)
/2324
31.2%
.1106
14.8%
:612
 
8.2%
-558
 
7.5%
0347
 
4.7%
1286
 
3.8%
8258
 
3.5%
2247
 
3.3%
4223
 
3.0%
9218
 
2.9%
Other values (15)1276
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII28820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/2324
 
8.1%
t2255
 
7.8%
s1528
 
5.3%
e1516
 
5.3%
w1325
 
4.6%
o1296
 
4.5%
.1106
 
3.8%
h1054
 
3.7%
i1032
 
3.6%
p990
 
3.4%
Other values (67)14394
49.9%

premiered
Categorical

HIGH CARDINALITY

Distinct399
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2020-12-04
 
16
2020-12-30
 
12
2020-12-18
 
8
2020-12-10
 
8
2020-12-16
 
8
Other values (394)
573 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6250
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)49.4%

Sample

1st row2019-03-25
2nd row2020-11-30
3rd row2019-12-17
4th row2020-10-13
5th row2020-03-08

Common Values

ValueCountFrequency (%)
2020-12-0416
 
2.6%
2020-12-3012
 
1.9%
2020-12-188
 
1.3%
2020-12-108
 
1.3%
2020-12-168
 
1.3%
2020-12-077
 
1.1%
2020-11-127
 
1.1%
2020-12-177
 
1.1%
2020-12-017
 
1.1%
2020-12-216
 
1.0%
Other values (389)539
86.2%

Length

2022-07-31T21:19:50.020976image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-0416
 
2.6%
2020-12-3012
 
1.9%
2020-12-188
 
1.3%
2020-12-108
 
1.3%
2020-12-168
 
1.3%
2020-12-077
 
1.1%
2020-11-127
 
1.1%
2020-12-177
 
1.1%
2020-12-017
 
1.1%
2020-11-236
 
1.0%
Other values (389)539
86.2%

Most occurring characters

ValueCountFrequency (%)
01588
25.4%
21431
22.9%
-1250
20.0%
11040
16.6%
9196
 
3.1%
3140
 
2.2%
8135
 
2.2%
7131
 
2.1%
4126
 
2.0%
6114
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number5000
80.0%
Dash Punctuation1250
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01588
31.8%
21431
28.6%
11040
20.8%
9196
 
3.9%
3140
 
2.8%
8135
 
2.7%
7131
 
2.6%
4126
 
2.5%
6114
 
2.3%
599
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
-1250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common6250
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01588
25.4%
21431
22.9%
-1250
20.0%
11040
16.6%
9196
 
3.1%
3140
 
2.2%
8135
 
2.2%
7131
 
2.1%
4126
 
2.0%
6114
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01588
25.4%
21431
22.9%
-1250
20.0%
11040
16.6%
9196
 
3.1%
3140
 
2.2%
8135
 
2.2%
7131
 
2.1%
4126
 
2.0%
6114
 
1.8%

rating_average
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)34.7%
Missing530
Missing (%)84.8%
Infinite0
Infinite (%)0.0%
Mean6.856842105
Minimum3.6
Maximum8.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:50.083687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3.6
5-th percentile5
Q16.45
median7.1
Q37.55
95-th percentile8.13
Maximum8.8
Range5.2
Interquartile range (IQR)1.1

Descriptive statistics

Standard deviation1.051913417
Coefficient of variation (CV)0.1534107685
Kurtosis0.6736403153
Mean6.856842105
Median Absolute Deviation (MAD)0.5
Skewness-0.9804789164
Sum651.4
Variance1.106521837
MonotonicityNot monotonic
2022-07-31T21:19:50.151792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
7.28
 
1.3%
7.56
 
1.0%
7.35
 
0.8%
6.85
 
0.8%
7.85
 
0.8%
55
 
0.8%
7.75
 
0.8%
6.94
 
0.6%
6.74
 
0.6%
74
 
0.6%
Other values (23)44
 
7.0%
(Missing)530
84.8%
ValueCountFrequency (%)
3.61
 
0.2%
41
 
0.2%
4.31
 
0.2%
4.41
 
0.2%
55
0.8%
5.21
 
0.2%
5.32
 
0.3%
5.42
 
0.3%
5.61
 
0.2%
5.81
 
0.2%
ValueCountFrequency (%)
8.81
 
0.2%
8.61
 
0.2%
8.23
0.5%
8.13
0.5%
83
0.5%
7.85
0.8%
7.75
0.8%
7.63
0.5%
7.56
1.0%
7.43
0.5%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct56
Distinct (%)13.6%
Missing214
Missing (%)34.2%
Infinite0
Infinite (%)0.0%
Mean37.46958637
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:50.222564image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q115
median30
Q345
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)30

Descriptive statistics

Standard deviation34.59128502
Coefficient of variation (CV)0.9231829964
Kurtosis13.86412607
Mean37.46958637
Median Absolute Deviation (MAD)15
Skewness3.028817028
Sum15400
Variance1196.557
MonotonicityNot monotonic
2022-07-31T21:19:50.297368image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3052
 
8.3%
6043
 
6.9%
4542
 
6.7%
1528
 
4.5%
2028
 
4.5%
2526
 
4.2%
1017
 
2.7%
5015
 
2.4%
514
 
2.2%
12014
 
2.2%
Other values (46)132
21.1%
(Missing)214
34.2%
ValueCountFrequency (%)
12
 
0.3%
24
 
0.6%
33
 
0.5%
42
 
0.3%
514
2.2%
63
 
0.5%
75
 
0.8%
87
1.1%
93
 
0.5%
1017
2.7%
ValueCountFrequency (%)
3001
 
0.2%
2401
 
0.2%
1806
 
1.0%
1301
 
0.2%
12014
 
2.2%
906
 
1.0%
661
 
0.2%
621
 
0.2%
6043
6.9%
581
 
0.2%

schedule_days
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct41
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
[]
179 
['Friday']
82 
['Thursday']
72 
['Monday']
49 
['Wednesday']
44 
Other values (36)
199 

Length

Max length78
Median length68
Mean length12.44
Min length2

Characters and Unicode

Total characters7775
Distinct characters22
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)2.6%

Sample

1st row['Monday', 'Wednesday', 'Friday']
2nd row['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']
3rd row['Saturday']
4th row['Tuesday']
5th row['Tuesday', 'Sunday']

Common Values

ValueCountFrequency (%)
[]179
28.6%
['Friday']82
13.1%
['Thursday']72
11.5%
['Monday']49
 
7.8%
['Wednesday']44
 
7.0%
['Sunday']38
 
6.1%
['Tuesday']38
 
6.1%
['Saturday']35
 
5.6%
['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']11
 
1.8%
['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']7
 
1.1%
Other values (31)70
 
11.2%

Length

2022-07-31T21:19:50.379613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
179
21.2%
thursday130
15.4%
friday124
14.7%
monday101
12.0%
wednesday99
11.7%
tuesday88
10.4%
sunday62
 
7.3%
saturday61
 
7.2%

Most occurring characters

ValueCountFrequency (%)
'1330
17.1%
d764
9.8%
a726
9.3%
y665
 
8.6%
[625
 
8.0%
]625
 
8.0%
u341
 
4.4%
s317
 
4.1%
r315
 
4.1%
e286
 
3.7%
Other values (12)1781
22.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4092
52.6%
Other Punctuation1549
 
19.9%
Uppercase Letter665
 
8.6%
Open Punctuation625
 
8.0%
Close Punctuation625
 
8.0%
Space Separator219
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d764
18.7%
a726
17.7%
y665
16.3%
u341
8.3%
s317
7.7%
r315
7.7%
e286
 
7.0%
n262
 
6.4%
h130
 
3.2%
i124
 
3.0%
Other values (2)162
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
T218
32.8%
F124
18.6%
S123
18.5%
M101
15.2%
W99
14.9%
Other Punctuation
ValueCountFrequency (%)
'1330
85.9%
,219
 
14.1%
Open Punctuation
ValueCountFrequency (%)
[625
100.0%
Close Punctuation
ValueCountFrequency (%)
]625
100.0%
Space Separator
ValueCountFrequency (%)
219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4757
61.2%
Common3018
38.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
d764
16.1%
a726
15.3%
y665
14.0%
u341
7.2%
s317
6.7%
r315
6.6%
e286
 
6.0%
n262
 
5.5%
T218
 
4.6%
h130
 
2.7%
Other values (7)733
15.4%
Common
ValueCountFrequency (%)
'1330
44.1%
[625
20.7%
]625
20.7%
,219
 
7.3%
219
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'1330
17.1%
d764
9.8%
a726
9.3%
y665
 
8.6%
[625
 
8.0%
]625
 
8.0%
u341
 
4.4%
s317
 
4.1%
r315
 
4.1%
e286
 
3.7%
Other values (12)1781
22.9%

schedule_time
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct44
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
467 
20:00
 
25
12:00
 
14
21:00
 
14
10:00
 
12
Other values (39)
93 

Length

Max length5
Median length0
Mean length1.264
Min length0

Characters and Unicode

Total characters790
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)4.0%

Sample

1st row
2nd row10:00
3rd row23:45
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
467
74.7%
20:0025
 
4.0%
12:0014
 
2.2%
21:0014
 
2.2%
10:0012
 
1.9%
06:0012
 
1.9%
22:009
 
1.4%
19:008
 
1.3%
18:007
 
1.1%
17:006
 
1.0%
Other values (34)51
 
8.2%

Length

2022-07-31T21:19:50.450414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0025
15.8%
21:0014
 
8.9%
12:0014
 
8.9%
10:0012
 
7.6%
06:0012
 
7.6%
22:009
 
5.7%
19:008
 
5.1%
18:007
 
4.4%
17:006
 
3.8%
00:006
 
3.8%
Other values (33)45
28.5%

Most occurring characters

ValueCountFrequency (%)
0358
45.3%
:158
20.0%
299
 
12.5%
188
 
11.1%
521
 
2.7%
815
 
1.9%
613
 
1.6%
313
 
1.6%
912
 
1.5%
78
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number632
80.0%
Other Punctuation158
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0358
56.6%
299
 
15.7%
188
 
13.9%
521
 
3.3%
815
 
2.4%
613
 
2.1%
313
 
2.1%
912
 
1.9%
78
 
1.3%
45
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common790
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0358
45.3%
:158
20.0%
299
 
12.5%
188
 
11.1%
521
 
2.7%
815
 
1.9%
613
 
1.6%
313
 
1.6%
912
 
1.5%
78
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII790
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0358
45.3%
:158
20.0%
299
 
12.5%
188
 
11.1%
521
 
2.7%
815
 
1.9%
613
 
1.6%
313
 
1.6%
912
 
1.5%
78
 
1.0%

show_id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46007.0064
Minimum802
Maximum63310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:50.516241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum802
5-th percentile15415.6
Q142843
median50983
Q352772
95-th percentile59574.2
Maximum63310
Range62508
Interquartile range (IQR)9929

Descriptive statistics

Standard deviation12763.03202
Coefficient of variation (CV)0.2774149638
Kurtosis2.58518717
Mean46007.0064
Median Absolute Deviation (MAD)3956
Skewness-1.717471738
Sum28754379
Variance162894986.2
MonotonicityNot monotonic
2022-07-31T21:19:50.593200image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
416481
 
0.2%
494841
 
0.2%
548371
 
0.2%
623061
 
0.2%
234011
 
0.2%
497211
 
0.2%
604271
 
0.2%
411921
 
0.2%
438831
 
0.2%
450901
 
0.2%
Other values (615)615
98.4%
ValueCountFrequency (%)
8021
0.2%
15961
0.2%
18251
0.2%
22661
0.2%
25041
0.2%
28551
0.2%
37341
0.2%
40911
0.2%
60901
0.2%
60971
0.2%
ValueCountFrequency (%)
633101
0.2%
631551
0.2%
629011
0.2%
627641
0.2%
625451
0.2%
624181
0.2%
623061
0.2%
621271
0.2%
619091
0.2%
617551
0.2%

status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Running
317 
Ended
219 
To Be Determined
89 

Length

Max length16
Median length7
Mean length7.5808
Min length5

Characters and Unicode

Total characters4738
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowTo Be Determined
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running317
50.7%
Ended219
35.0%
To Be Determined89
 
14.2%

Length

2022-07-31T21:19:50.664288image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-07-31T21:19:50.726394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
running317
39.5%
ended219
27.3%
to89
 
11.1%
be89
 
11.1%
determined89
 
11.1%

Most occurring characters

ValueCountFrequency (%)
n1259
26.6%
e575
12.1%
d527
11.1%
i406
 
8.6%
R317
 
6.7%
u317
 
6.7%
g317
 
6.7%
E219
 
4.6%
178
 
3.8%
T89
 
1.9%
Other values (6)534
11.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3757
79.3%
Uppercase Letter803
 
16.9%
Space Separator178
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n1259
33.5%
e575
15.3%
d527
14.0%
i406
 
10.8%
u317
 
8.4%
g317
 
8.4%
o89
 
2.4%
t89
 
2.4%
r89
 
2.4%
m89
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
R317
39.5%
E219
27.3%
T89
 
11.1%
B89
 
11.1%
D89
 
11.1%
Space Separator
ValueCountFrequency (%)
178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4560
96.2%
Common178
 
3.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n1259
27.6%
e575
12.6%
d527
11.6%
i406
 
8.9%
R317
 
7.0%
u317
 
7.0%
g317
 
7.0%
E219
 
4.8%
T89
 
2.0%
o89
 
2.0%
Other values (5)445
 
9.8%
Common
ValueCountFrequency (%)
178
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n1259
26.6%
e575
12.1%
d527
11.1%
i406
 
8.6%
R317
 
6.7%
u317
 
6.7%
g317
 
6.7%
E219
 
4.6%
178
 
3.8%
T89
 
1.9%
Other values (6)534
11.3%

summary
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct549
Distinct (%)100.0%
Missing76
Missing (%)12.2%
Memory size5.0 KiB
<p>"Secretly loving your close friend and changing him to be the love one" is an uncomfortable feeling for Sine and Tan. They don't know each person's thoughts. Will their relationship be the same after love confession? Hoping this love will be calculated with the correct answer.</p>
 
1
<p><b>Just Roll With It</b> is an interactive improvisational comedy centered around the blended Bennett-Blatt family and features step-siblings Blair and Owen who could not be more different. Blair, often a rebel without a cause, is the polar opposite of her strict, regimented, ex-military mom Rachel. Owen, a born athlete with a taste for scheduling and organization, is always trying to clean up Byron, his creative and charismatic morning-radio-show-host father. Despite their differences, the Bennett-Blatt clan, and the actors who play them, know how to take whatever life – and the studio audience – throws at them.</p>
 
1
<p>Each week <b>The Amber Ruffin Show</b> will showcase Amber's signature smart-and-silly take on the week. A late-night show with just the good parts – the comedy.</p>
 
1
<p><b>Bare Knuckle Fighting Championship</b> is an American bare-knuckle boxing promotion based in Philadelphia. BKFC is the first promotion to hold an official state sanctioned and commissioned bare-knuckle boxing event in America since 1889. Its first event was held in 2018, with 10 "numbered" events held as of Feb 2020.</p>
 
1
<p>Proving once again that "the drive-in will never die," iconic horror host and exploitation movie aficionado Joe Bob Briggs is back with an all-new Shudder Original series, hosting weekly Friday night double features streaming live exclusively on Shudder. Every week, The Last Drive-In series offers an eclectic pairing of films, with selections ranging across five decades and running the gamut from horror classics to obscurities and foreign cult favorites. And from time to time, special surprise guests will drop in on Joe Bob and Darcy the Mail Girl.</p>
 
1
Other values (544)
544 

Length

Max length1620
Median length464
Mean length331.0619308
Min length36

Characters and Unicode

Total characters181753
Distinct characters173
Distinct categories15 ?
Distinct scripts5 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique549 ?
Unique (%)100.0%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>
3rd row<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>
4th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>
5th row<p>It's spin-off drama of <b>"Kono Koi Atatamemasu ka"</b></p>

Common Values

ValueCountFrequency (%)
<p>"Secretly loving your close friend and changing him to be the love one" is an uncomfortable feeling for Sine and Tan. They don't know each person's thoughts. Will their relationship be the same after love confession? Hoping this love will be calculated with the correct answer.</p>1
 
0.2%
<p><b>Just Roll With It</b> is an interactive improvisational comedy centered around the blended Bennett-Blatt family and features step-siblings Blair and Owen who could not be more different. Blair, often a rebel without a cause, is the polar opposite of her strict, regimented, ex-military mom Rachel. Owen, a born athlete with a taste for scheduling and organization, is always trying to clean up Byron, his creative and charismatic morning-radio-show-host father. Despite their differences, the Bennett-Blatt clan, and the actors who play them, know how to take whatever life – and the studio audience – throws at them.</p>1
 
0.2%
<p>Each week <b>The Amber Ruffin Show</b> will showcase Amber's signature smart-and-silly take on the week. A late-night show with just the good parts – the comedy.</p>1
 
0.2%
<p><b>Bare Knuckle Fighting Championship</b> is an American bare-knuckle boxing promotion based in Philadelphia. BKFC is the first promotion to hold an official state sanctioned and commissioned bare-knuckle boxing event in America since 1889. Its first event was held in 2018, with 10 "numbered" events held as of Feb 2020.</p>1
 
0.2%
<p>Proving once again that "the drive-in will never die," iconic horror host and exploitation movie aficionado Joe Bob Briggs is back with an all-new Shudder Original series, hosting weekly Friday night double features streaming live exclusively on Shudder. Every week, The Last Drive-In series offers an eclectic pairing of films, with selections ranging across five decades and running the gamut from horror classics to obscurities and foreign cult favorites. And from time to time, special surprise guests will drop in on Joe Bob and Darcy the Mail Girl.</p>1
 
0.2%
<p>Mount Olympus is the divine sanctuary created by the Titans for the young gods and goddesses, Among the young immortals, one young goddess, Eris, is a black sheep. She has an horrible reputation, she doesn't fit the high standards of Mount Olympus and she is is being avoid like the plague. But her meeting with a mortal is going to change her divine destiny.</p>1
 
0.2%
<p>Tops is a young man who has been fascinated by cooking since childhood. He finds happiness in cooking delicious and tasty food with great care. Marwin is young, romantic, playful, and charming. He loves and is dedicated to music and dreams of becoming a world-class musician. His interest in music is so strong that he didn't take care of himself until he came to live with Tops. When the difference between the two becomes the perfect combination, chaos ensues, and the two find themselves deciding between their dreams and each other. This mini series tells the story of two friends who return to each other's lives during their last year of school and help make one another's dreams come true.</p>1
 
0.2%
<p><b>ICW No Holds Barred</b> (fka Impact Championship Wrestling) is a Professional Wrestling Promotion based out of Queens, New York founded in 2001 to showcase the best competition in American Pro-Wrestling Today.</p>1
 
0.2%
<p>A relationship drama about two young people who fall in love at a difficult time in life. In the series, we meet Anders and Mio who, after a one night stand, find out that they are pregnant.</p>1
 
0.2%
<p>Are ghosts and demons dwelling among us? The Fourman Brothers, a family of paranormal investigators, investigate hauntings.</p>1
 
0.2%
Other values (539)539
86.2%
(Missing)76
 
12.2%

Length

2022-07-31T21:19:50.805880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the1734
 
5.8%
and1070
 
3.6%
of868
 
2.9%
a836
 
2.8%
to741
 
2.5%
in548
 
1.8%
is397
 
1.3%
with305
 
1.0%
on224
 
0.8%
his219
 
0.7%
Other values (7609)22882
76.7%

Most occurring characters

ValueCountFrequency (%)
29208
16.1%
e17024
 
9.4%
t11431
 
6.3%
a11054
 
6.1%
o10509
 
5.8%
n10182
 
5.6%
i10171
 
5.6%
s9358
 
5.1%
r8873
 
4.9%
h7120
 
3.9%
Other values (163)56823
31.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter137830
75.8%
Space Separator29292
 
16.1%
Uppercase Letter5271
 
2.9%
Other Punctuation4879
 
2.7%
Math Symbol3343
 
1.8%
Decimal Number534
 
0.3%
Dash Punctuation458
 
0.3%
Open Punctuation50
 
< 0.1%
Close Punctuation50
 
< 0.1%
Other Letter21
 
< 0.1%
Other values (5)25
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e17024
12.4%
t11431
 
8.3%
a11054
 
8.0%
o10509
 
7.6%
n10182
 
7.4%
i10171
 
7.4%
s9358
 
6.8%
r8873
 
6.4%
h7120
 
5.2%
l5694
 
4.1%
Other values (66)36414
26.4%
Uppercase Letter
ValueCountFrequency (%)
T554
 
10.5%
S428
 
8.1%
A383
 
7.3%
W317
 
6.0%
C314
 
6.0%
M261
 
5.0%
H256
 
4.9%
B223
 
4.2%
F200
 
3.8%
L200
 
3.8%
Other values (24)2135
40.5%
Other Letter
ValueCountFrequency (%)
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
1
 
4.8%
Other values (11)11
52.4%
Other Punctuation
ValueCountFrequency (%)
,1716
35.2%
.1469
30.1%
/869
17.8%
'375
 
7.7%
"176
 
3.6%
!90
 
1.8%
:65
 
1.3%
?64
 
1.3%
;29
 
0.6%
&11
 
0.2%
Other values (4)15
 
0.3%
Decimal Number
ValueCountFrequency (%)
0133
24.9%
1109
20.4%
298
18.4%
956
10.5%
529
 
5.4%
328
 
5.2%
827
 
5.1%
422
 
4.1%
721
 
3.9%
611
 
2.1%
Math Symbol
ValueCountFrequency (%)
<1671
50.0%
>1671
50.0%
+1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
-417
91.0%
22
 
4.8%
19
 
4.1%
Space Separator
ValueCountFrequency (%)
29208
99.7%
 84
 
0.3%
Open Punctuation
ValueCountFrequency (%)
(49
98.0%
[1
 
2.0%
Close Punctuation
ValueCountFrequency (%)
)49
98.0%
]1
 
2.0%
Currency Symbol
ValueCountFrequency (%)
$4
80.0%
1
 
20.0%
Format
ValueCountFrequency (%)
14
100.0%
Initial Punctuation
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin142693
78.5%
Common38631
 
21.3%
Cyrillic408
 
0.2%
Han17
 
< 0.1%
Katakana4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e17024
11.9%
t11431
 
8.0%
a11054
 
7.7%
o10509
 
7.4%
n10182
 
7.1%
i10171
 
7.1%
s9358
 
6.6%
r8873
 
6.2%
h7120
 
5.0%
l5694
 
4.0%
Other values (65)41277
28.9%
Common
ValueCountFrequency (%)
29208
75.6%
,1716
 
4.4%
<1671
 
4.3%
>1671
 
4.3%
.1469
 
3.8%
/869
 
2.2%
-417
 
1.1%
'375
 
1.0%
"176
 
0.5%
0133
 
0.3%
Other values (32)926
 
2.4%
Cyrillic
ValueCountFrequency (%)
е39
 
9.6%
о38
 
9.3%
и38
 
9.3%
т38
 
9.3%
а26
 
6.4%
с26
 
6.4%
н24
 
5.9%
м23
 
5.6%
в16
 
3.9%
р15
 
3.7%
Other values (25)125
30.6%
Han
ValueCountFrequency (%)
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (7)7
41.2%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII181101
99.6%
Cyrillic408
 
0.2%
None154
 
0.1%
Punctuation66
 
< 0.1%
CJK17
 
< 0.1%
Katakana5
 
< 0.1%
Currency Symbols1
 
< 0.1%
Dingbats1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29208
16.1%
e17024
 
9.4%
t11431
 
6.3%
a11054
 
6.1%
o10509
 
5.8%
n10182
 
5.6%
i10171
 
5.6%
s9358
 
5.2%
r8873
 
4.9%
h7120
 
3.9%
Other values (75)56171
31.0%
None
ValueCountFrequency (%)
 84
54.5%
é12
 
7.8%
ä10
 
6.5%
ö6
 
3.9%
ø6
 
3.9%
ü5
 
3.2%
á4
 
2.6%
å4
 
2.6%
Í3
 
1.9%
Å2
 
1.3%
Other values (14)18
 
11.7%
Cyrillic
ValueCountFrequency (%)
е39
 
9.6%
о38
 
9.3%
и38
 
9.3%
т38
 
9.3%
а26
 
6.4%
с26
 
6.4%
н24
 
5.9%
м23
 
5.6%
в16
 
3.9%
р15
 
3.7%
Other values (25)125
30.6%
Punctuation
ValueCountFrequency (%)
22
33.3%
19
28.8%
14
21.2%
7
 
10.6%
4
 
6.1%
Currency Symbols
ValueCountFrequency (%)
1
100.0%
Dingbats
ValueCountFrequency (%)
1
100.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
CJK
ValueCountFrequency (%)
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (7)7
41.2%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Scripted
265 
Documentary
87 
Animation
85 
Talk Show
62 
Reality
56 
Other values (6)
70 

Length

Max length11
Median length10
Mean length8.456
Min length4

Characters and Unicode

Total characters5285
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowReality
2nd rowScripted
3rd rowDocumentary
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted265
42.4%
Documentary87
 
13.9%
Animation85
 
13.6%
Talk Show62
 
9.9%
Reality56
 
9.0%
Variety24
 
3.8%
Sports21
 
3.4%
Game Show15
 
2.4%
News6
 
1.0%
Award Show3
 
0.5%

Length

2022-07-31T21:19:50.884692image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scripted265
37.5%
documentary87
 
12.3%
animation85
 
12.0%
show81
 
11.5%
talk62
 
8.8%
reality56
 
7.9%
variety24
 
3.4%
sports21
 
3.0%
game15
 
2.1%
news6
 
0.8%
Other values (2)4
 
0.6%

Most occurring characters

ValueCountFrequency (%)
t538
 
10.2%
i515
 
9.7%
e454
 
8.6%
r400
 
7.6%
S367
 
6.9%
c352
 
6.7%
a333
 
6.3%
p286
 
5.4%
o274
 
5.2%
d268
 
5.1%
Other values (18)1498
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4498
85.1%
Uppercase Letter706
 
13.4%
Space Separator81
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t538
12.0%
i515
11.4%
e454
10.1%
r400
8.9%
c352
7.8%
a333
7.4%
p286
 
6.4%
o274
 
6.1%
d268
 
6.0%
n258
 
5.7%
Other values (8)820
18.2%
Uppercase Letter
ValueCountFrequency (%)
S367
52.0%
A88
 
12.5%
D87
 
12.3%
T62
 
8.8%
R56
 
7.9%
V24
 
3.4%
G15
 
2.1%
N6
 
0.8%
P1
 
0.1%
Space Separator
ValueCountFrequency (%)
81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5204
98.5%
Common81
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t538
 
10.3%
i515
 
9.9%
e454
 
8.7%
r400
 
7.7%
S367
 
7.1%
c352
 
6.8%
a333
 
6.4%
p286
 
5.5%
o274
 
5.3%
d268
 
5.1%
Other values (17)1417
27.2%
Common
ValueCountFrequency (%)
81
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5285
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t538
 
10.2%
i515
 
9.7%
e454
 
8.6%
r400
 
7.6%
S367
 
6.9%
c352
 
6.7%
a333
 
6.3%
p286
 
5.4%
o274
 
5.2%
d268
 
5.1%
Other values (18)1498
28.3%

updated
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1638604640
Minimum1602172227
Maximum1659299828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:50.953544image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1602172227
5-th percentile1608706464
Q11621111886
median1644650582
Q31653930560
95-th percentile1658900558
Maximum1659299828
Range57127601
Interquartile range (IQR)32818674

Descriptive statistics

Standard deviation17769668.08
Coefficient of variation (CV)0.01084439019
Kurtosis-1.200334513
Mean1638604640
Median Absolute Deviation (MAD)12201916
Skewness-0.5512415508
Sum1.0241279 × 1012
Variance3.157611035 × 1014
MonotonicityNot monotonic
2022-07-31T21:19:51.029924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16084990071
 
0.2%
16398364991
 
0.2%
16200179501
 
0.2%
16586688971
 
0.2%
16250336671
 
0.2%
16574757231
 
0.2%
16480547571
 
0.2%
16382107271
 
0.2%
16592018061
 
0.2%
16569636991
 
0.2%
Other values (615)615
98.4%
ValueCountFrequency (%)
16021722271
0.2%
16034670371
0.2%
16045871191
0.2%
16045871451
0.2%
16071040921
0.2%
16071675851
0.2%
16072788871
0.2%
16073820731
0.2%
16074646181
0.2%
16075487681
0.2%
ValueCountFrequency (%)
16592998281
0.2%
16592804271
0.2%
16592803511
0.2%
16592800121
0.2%
16592617021
0.2%
16592609061
0.2%
16592388311
0.2%
16592097411
0.2%
16592018061
0.2%
16591909651
0.2%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct625
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
https://www.tvmaze.com/shows/41648/sim-for-you
 
1
https://www.tvmaze.com/shows/49484/bare-knuckle-fighting-championship
 
1
https://www.tvmaze.com/shows/54837/my-lecturer-my-husband
 
1
https://www.tvmaze.com/shows/62306/rainbow-high
 
1
https://www.tvmaze.com/shows/23401/mickey-mouse-mixed-up-adventures
 
1
Other values (620)
620 

Length

Max length85
Median length69
Mean length51.208
Min length38

Characters and Unicode

Total characters32005
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique625 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/52198/kotiki
3rd rowhttps://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym
4th rowhttps://www.tvmaze.com/shows/51336/core-sense
5th rowhttps://www.tvmaze.com/shows/54033/wu-shen-zhu-zai

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/41648/sim-for-you1
 
0.2%
https://www.tvmaze.com/shows/49484/bare-knuckle-fighting-championship1
 
0.2%
https://www.tvmaze.com/shows/54837/my-lecturer-my-husband1
 
0.2%
https://www.tvmaze.com/shows/62306/rainbow-high1
 
0.2%
https://www.tvmaze.com/shows/23401/mickey-mouse-mixed-up-adventures1
 
0.2%
https://www.tvmaze.com/shows/49721/madagascar-a-little-wild1
 
0.2%
https://www.tvmaze.com/shows/60427/justimus-esittaa-duo1
 
0.2%
https://www.tvmaze.com/shows/41192/just-roll-with-it1
 
0.2%
https://www.tvmaze.com/shows/43883/the-amber-ruffin-show1
 
0.2%
https://www.tvmaze.com/shows/45090/the-last-drive-in-with-joe-bob-briggs1
 
0.2%
Other values (615)615
98.4%

Length

2022-07-31T21:19:51.114983image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/41648/sim-for-you1
 
0.2%
https://www.tvmaze.com/shows/55016/ling-jian-zun1
 
0.2%
https://www.tvmaze.com/shows/52984/konusanlar1
 
0.2%
https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym1
 
0.2%
https://www.tvmaze.com/shows/51336/core-sense1
 
0.2%
https://www.tvmaze.com/shows/54033/wu-shen-zhu-zai1
 
0.2%
https://www.tvmaze.com/shows/61674/sono-koi-mousukoshi-atatamemasuka1
 
0.2%
https://www.tvmaze.com/shows/52038/please-wait-brother1
 
0.2%
https://www.tvmaze.com/shows/52373/fearless-whispers1
 
0.2%
https://www.tvmaze.com/shows/57339/mafia-nights1
 
0.2%
Other values (615)615
98.4%

Most occurring characters

ValueCountFrequency (%)
/3125
 
9.8%
w2642
 
8.3%
t2526
 
7.9%
s2510
 
7.8%
o1915
 
6.0%
e1672
 
5.2%
h1594
 
5.0%
m1544
 
4.8%
a1395
 
4.4%
.1250
 
3.9%
Other values (30)11832
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter22698
70.9%
Other Punctuation5000
 
15.6%
Decimal Number3173
 
9.9%
Dash Punctuation1134
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w2642
11.6%
t2526
11.1%
s2510
11.1%
o1915
 
8.4%
e1672
 
7.4%
h1594
 
7.0%
m1544
 
6.8%
a1395
 
6.1%
c875
 
3.9%
p798
 
3.5%
Other values (16)5227
23.0%
Decimal Number
ValueCountFrequency (%)
5544
17.1%
4402
12.7%
2340
10.7%
1339
10.7%
3308
9.7%
0270
8.5%
6263
8.3%
9251
7.9%
8241
7.6%
7215
 
6.8%
Other Punctuation
ValueCountFrequency (%)
/3125
62.5%
.1250
 
25.0%
:625
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-1134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin22698
70.9%
Common9307
29.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w2642
11.6%
t2526
11.1%
s2510
11.1%
o1915
 
8.4%
e1672
 
7.4%
h1594
 
7.0%
m1544
 
6.8%
a1395
 
6.1%
c875
 
3.9%
p798
 
3.5%
Other values (16)5227
23.0%
Common
ValueCountFrequency (%)
/3125
33.6%
.1250
 
13.4%
-1134
 
12.2%
:625
 
6.7%
5544
 
5.8%
4402
 
4.3%
2340
 
3.7%
1339
 
3.6%
3308
 
3.3%
0270
 
2.9%
Other values (4)970
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII32005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/3125
 
9.8%
w2642
 
8.3%
t2526
 
7.9%
s2510
 
7.8%
o1915
 
6.0%
e1672
 
5.2%
h1594
 
5.0%
m1544
 
4.8%
a1395
 
4.4%
.1250
 
3.9%
Other values (30)11832
37.0%

webChannel_id
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct138
Distinct (%)22.7%
Missing17
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean150.0197368
Minimum1
Maximum533
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:51.189699image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q121
median103.5
Q3281
95-th percentile416.65
Maximum533
Range532
Interquartile range (IQR)260

Descriptive statistics

Standard deviation145.9210127
Coefficient of variation (CV)0.9726787673
Kurtosis-0.8046353534
Mean150.0197368
Median Absolute Deviation (MAD)82.5
Skewness0.7186437536
Sum91212
Variance21292.94195
MonotonicityNot monotonic
2022-07-31T21:19:51.269678image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21145
23.2%
138
 
6.1%
10426
 
4.2%
23825
 
4.0%
315
 
2.4%
17312
 
1.9%
32912
 
1.9%
6712
 
1.9%
8811
 
1.8%
1510
 
1.6%
Other values (128)302
48.3%
(Missing)17
 
2.7%
ValueCountFrequency (%)
138
 
6.1%
23
 
0.5%
315
 
2.4%
123
 
0.5%
1510
 
1.6%
203
 
0.5%
21145
23.2%
221
 
0.2%
265
 
0.8%
309
 
1.4%
ValueCountFrequency (%)
5331
0.2%
5182
0.3%
5161
0.2%
5101
0.2%
5071
0.2%
5061
0.2%
4981
0.2%
4932
0.3%
4711
0.2%
4641
0.2%

weight
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct100
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.6752
Minimum0
Maximum100
Zeros7
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size5.0 KiB
2022-07-31T21:19:51.349875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q114
median32
Q356
95-th percentile92
Maximum100
Range100
Interquartile range (IQR)42

Descriptive statistics

Standard deviation27.72608306
Coefficient of variation (CV)0.7359239782
Kurtosis-0.6310272473
Mean37.6752
Median Absolute Deviation (MAD)19
Skewness0.6699074547
Sum23547
Variance768.7356821
MonotonicityNot monotonic
2022-07-31T21:19:51.429311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2028
 
4.5%
826
 
4.2%
1221
 
3.4%
1117
 
2.7%
3216
 
2.6%
716
 
2.6%
314
 
2.2%
2914
 
2.2%
1313
 
2.1%
3913
 
2.1%
Other values (90)447
71.5%
ValueCountFrequency (%)
07
 
1.1%
112
1.9%
24
 
0.6%
314
2.2%
45
 
0.8%
57
 
1.1%
69
 
1.4%
716
2.6%
826
4.2%
92
 
0.3%
ValueCountFrequency (%)
1002
 
0.3%
993
 
0.5%
982
 
0.3%
974
0.6%
964
0.6%
954
0.6%
949
1.4%
933
 
0.5%
923
 
0.5%
913
 
0.5%

Interactions

2022-07-31T21:19:47.722320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:43.882781image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.428921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.887438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.358971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.856852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.640658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.189478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.823010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:43.960790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.488342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.944801image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.428325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.923165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.713800image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.257388image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.882811image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.023608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.546304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.004588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.489745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.229033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.778043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.318522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.955112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.089124image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.604756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.061832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.543090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.288725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.838299image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.376212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:48.017904image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.159687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.662805image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.117361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.607034image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.355870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.907622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.441690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:48.085018image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.229720image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.720058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.175581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.671751image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.427426image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.980877image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.512598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:48.213617image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.300054image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.777073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.235875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.735995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.501929image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.053722image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.585232image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:48.295385image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.365192image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:44.832118image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.292845image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:45.797082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:46.570589image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.121661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-07-31T21:19:47.651828image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-07-31T21:19:51.500454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-07-31T21:19:51.600997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-07-31T21:19:51.700426image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-07-31T21:19:51.789423image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-07-31T21:19:51.868495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-07-31T21:19:48.476531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-07-31T21:19:48.749861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-07-31T21:19:48.902670image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-07-31T21:19:49.025229image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

show_idurlnametypelanguagegenresstatusruntimeaverageRuntimepremieredendedofficialSiteschedule_timeschedule_daysrating_averageweightnetworksummaryupdatedimagelinks_self_hreflinks_previousepisode_hreflinks_nextepisode_hrefwebChannel_idnetwork_id
041648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/121637['Monday', 'Wednesday', 'Friday']NaN63NaN<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007NaNhttps://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaN122.0NaN
152198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian['Comedy']Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki10:00['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday']NaN11NaNNone1637555191NaNhttps://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873NaN510.0NaN
252933https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevymLAB с Антоном БеляевымDocumentaryRussian['Music']To Be Determined26.025.02019-12-17Nonehttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva23:45['Saturday']NaN40NaN<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>1654035738NaNhttps://api.tvmaze.com/shows/52933https://api.tvmaze.com/episodes/2245512NaN381.0308.0
351336https://www.tvmaze.com/shows/51336/core-senseCore SenseAnimationChinese['Action', 'Anime', 'Science-Fiction']Running24.024.02020-10-13Nonehttps://www.bilibili.com/bangumi/media/md2822306410:00['Tuesday']NaN31NaN<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>1604587119NaNhttps://api.tvmaze.com/shows/51336https://api.tvmaze.com/episodes/1964569NaN51.0NaN
454033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese['Action', 'Adventure', 'Anime', 'Fantasy']Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00['Tuesday', 'Sunday']NaN81NaN<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444NaNhttps://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309431https://api.tvmaze.com/episodes/2309432104.0NaN
561674https://www.tvmaze.com/shows/61674/sono-koi-mousukoshi-atatamemasukaSono koi Mousukoshi AtatamemasukaScriptedJapanese['Romance']Ended15.015.02020-10-202020-12-22https://www.paravi.jp/static/koisuko22:00['Tuesday']NaN1NaN<p>It's spin-off drama of <b>"Kono Koi Atatamemasu ka"</b></p>1650915213NaNhttps://api.tvmaze.com/shows/61674https://api.tvmaze.com/episodes/2315117NaN342.0NaN
652038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese['Comedy']Ended37.037.02020-11-172020-12-08None12:00['Tuesday', 'Wednesday', 'Thursday']NaN48NaNNone1607697965NaNhttps://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaN104.0NaN
752373https://www.tvmaze.com/shows/52373/fearless-whispersFearless WhispersScriptedChinese['Drama', 'Romance', 'History']Ended60.060.02020-11-062020-12-01None['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']NaN11NaN<p>A story revolving around a fresh graduate who holds an idealistic view of what's right and wrong, yet realizes that the very institution he chose to serve falls heavily onto a gray area caught in the struggles during chaotic times.</p>1607717005NaNhttps://api.tvmaze.com/shows/52373https://api.tvmaze.com/episodes/1984264NaNNaN1282.0
855016https://www.tvmaze.com/shows/55016/ling-jian-zunLing Jian ZunAnimationChinese['Anime']Running10.010.02019-01-15Nonehttps://v.qq.com/x/cover/2w2legt0g8z26al.html['Tuesday', 'Friday']NaN52NaN<p>The strong man was attacked and returned to his youth. He became the weakest waste young lord. He will never let go of the enemy of the previous life in this life and must make up the regret of the previous life in this life! By the time the Spirit Sword is powerful, the protagonist will be supreme in the three worlds between heaven and earth! If there is someone doesn't obey him, he will kill him with the sword!</p><p><br /> </p>1653895786NaNhttps://api.tvmaze.com/shows/55016https://api.tvmaze.com/episodes/2336755NaN104.0NaN
957339https://www.tvmaze.com/shows/57339/mafia-nightsMafia NightsRealityPersian[]Running90.090.02020-11-17NoneNone08:00['Sunday']NaN6NaN<p><b>Mafia Nights</b> is an Iranian television series in the family, social and enigmatic genres, directed by Saeid Aboutaleb. This series is based on the Mafia game. In each season of this series, one of the film and television actors invites 12 of his friends to play Mafia, and they, together with Mohammad Reza Alimardani, who is called the leader or organizer of the game, make the game completely real without the intervention of the directing team. They do. It started broadcasting on Tuesday, November 18, 2020 on the home theater network and will be distributed weekly on Tuesdays.</p><p><br /> </p>1655911775NaNhttps://api.tvmaze.com/shows/57339https://api.tvmaze.com/episodes/2299087NaN507.0NaN

Last rows

show_idurlnametypelanguagegenresstatusruntimeaverageRuntimepremieredendedofficialSiteschedule_timeschedule_daysrating_averageweightnetworksummaryupdatedimagelinks_self_hreflinks_previousepisode_hreflinks_nextepisode_hrefwebChannel_idnetwork_id
61555288https://www.tvmaze.com/shows/55288/lord-xue-yingLord Xue YingAnimationChinese[]Running20.020.02018-12-20Nonehttps://v.qq.com/detail/s/sifd2an7kx2h9h8.html['Monday']NaN17NaN<p>In the Tranquil Sun province of the empire, there exists an unremarkable lordship known as Xue Ying Territory! This is the home of the Dong Bo clan, the clan of our hero Xue Ying! His father, a commoner turned noble; his mother, a noble who abandoned her clan for love, and his brother, an innocent toddler. But peace cannot last forever, Xue Ying's peaceful life is shattered, and the only way to reclaim it is through power! (Source: Novel Updates)</p><p><br /> </p>1648280587NaNhttps://api.tvmaze.com/shows/55288https://api.tvmaze.com/episodes/2301754NaN104.0NaN
61644343https://www.tvmaze.com/shows/44343/aynen-aynenAynen AynenScriptedTurkish['Comedy', 'Romance']Running5.07.02019-08-01Nonehttps://www.blutv.com/int/diziler/yerli/aynen-aynen['Friday']NaN37NaN<p>The series tells the story of Emir and Nil's entertaining relationship by explaining the relationship between men and women in a humorous as well as realistic language. We see the situations in which Nil and Emir want to show themselves to the other party in the relationship and in fact their own real thoughts.</p>1644468481NaNhttps://api.tvmaze.com/shows/44343https://api.tvmaze.com/episodes/2132467NaN222.0NaN
61719355https://www.tvmaze.com/shows/19355/loudermilkLoudermilkScriptedEnglish['Comedy']To Be DeterminedNaN30.02017-10-17NoneNone[]6.894NaN<p>This series centers on <b>Loudermilk </b>who is a recovering alcoholic and substance-abuse counselor with an extremely bad attitude about everything. He is unapologetically uncensored and has managed to piss off everyone. Although he has his drinking under control, Loudermilk's life is one step forward and 12 steps backwards.</p>1633453569NaNhttps://api.tvmaze.com/shows/19355https://api.tvmaze.com/episodes/1998683NaN3.0NaN
61832649https://www.tvmaze.com/shows/32649/chilling-adventures-of-sabrinaChilling Adventures of SabrinaScriptedEnglish['Horror', 'Romance', 'Supernatural']EndedNaN57.02018-10-262020-12-31https://www.netflix.com/title/80223989[]7.597NaN<p><b>Chilling Adventures of Sabrina</b> reimagines the origin &amp; adventures of Sabrina the Teenage Witch as a dark coming-of-age story that traffics in horror, the occult and, of course, witchcraft. This adaptation finds Sabrina wrestling to reconcile her dual nature —half-witch, half-mortal — while standing against the evil forces that threaten her, her family and the daylight world humans inhabit.</p>1656613542NaNhttps://api.tvmaze.com/shows/32649https://api.tvmaze.com/episodes/1949336NaN1.0NaN
61934187https://www.tvmaze.com/shows/34187/super-power-beat-downSuper Power Beat DownScriptedNone[]Running10.010.02012-03-15NoneNone[]NaN34NaNNone1609438777NaNhttps://api.tvmaze.com/shows/34187https://api.tvmaze.com/episodes/1996786NaN21.0NaN
62051826https://www.tvmaze.com/shows/51826/strange-heartStrange HeartScriptedTagalog['Drama', 'Romance']Ended25.026.02020-10-262020-12-31https://www.youtube.com/playlist?list=PLJPWxm3cDzKIgxaWEF4BxAhgqBheqMBxs[]NaN11NaN<p>They said, there's nothing wrong about love. But what if it is against our culture?</p><p><b>Strange Heart </b>is a story about family, love, and destiny. This will address some of the cultural issues about same-sex relationship. It shows the supremacy of love that really answers all the uncertainties and addresses the challenges through acceptance. </p><p>Love is inevitable and irreversible. Kristof and Joshua will face this reality as if nobody is in-charge, no matter what it takes.</p>1616293828NaNhttps://api.tvmaze.com/shows/51826https://api.tvmaze.com/episodes/2050241NaN21.0NaN
62152847https://www.tvmaze.com/shows/52847/three-men-four-wheelsThree Men Four WheelsRealityEnglish[]RunningNaNNaN2020-12-31Nonehttps://www.discoveryplus.co.uk/show/three-men-four-wheels[]NaN35NaN<p>Antique and classic car dealer Drew Pritchard, motoring broadcaster Andy Jaye and racing driver Marino Franchitti set out to discover the greatest racing cars of all time.</p>1611132125NaNhttps://api.tvmaze.com/shows/52847https://api.tvmaze.com/episodes/2001674NaN173.0NaN
62253581https://www.tvmaze.com/shows/53581/thursday-nightThursday NightTalk ShowArabic['Comedy', 'Family', 'Music']Running60.060.02020-12-31Nonehttps://shahid.mbc.net/en/shows/Laylat-Al-Khamis/show-82726123:00['Thursday']NaN21NaN<p>Join Yasmin Ezz and her celebrity guests as they sing, laugh and exchange stories in her latest talk show, <b>Thursday Night</b>.</p>1615629856NaNhttps://api.tvmaze.com/shows/53581https://api.tvmaze.com/episodes/2046124NaN379.01808.0
62359380https://www.tvmaze.com/shows/59380/forteresses-assiegees-batailles-de-legendeForteresses assiégées, batailles de légendeDocumentaryFrench[]Running51.052.02020-12-31Nonehttps://www.zed.fr/fr/tv/distribution/catalogue/programme/forteresses-assiegees-batailles-de-legende['Thursday']NaN1NaN<p>Built at strategic points, and fitted with impressive fortifications and ingenious systems to counter attacks, fortresses are thought to be impenetrable. And yet, certain skillful warlords have successfully stormed them. How did they manage this?</p><p>By recounting how some of the most remarkable sieges - in ancient times or in medieval history - played out, this series revisits the construction of these megastructures and reveals the different strategies used to lay or to endure a siege. Thanks to CGI, dramatized scenes, and with the help of key experts, it immerses us in the compelling confrontation between the construction genius of the military strategists and the ingenuity of some exceptional warriors.</p>1639070620NaNhttps://api.tvmaze.com/shows/59380https://api.tvmaze.com/episodes/2234297NaN188.0NaN
62439441https://www.tvmaze.com/shows/39441/carl-webers-the-family-businessCarl Weber's The Family BusinessScriptedEnglish['Drama', 'Crime', 'Thriller']Running60.060.02018-11-13Nonehttps://www.bet.plus/shows/the-family-business21:00[]5.094NaN<p>Meet the Duncans, a prominent family from Jamaica, Queens living fast and luxurious. By day, they're an upstanding family; by night, they live a dangerous secret life. The patriarch of the family, L.C. Duncan, is at the age when he's starting to think about retirement and has to decide which of his children should take over his thriving exotic car dealership. The Duncans quickly come under siege from some of the top politicians, mafia and drug cartels in the city. The Duncans will have to stick together or die separately.</p>1638411895NaNhttps://api.tvmaze.com/shows/39441https://api.tvmaze.com/episodes/2194257NaN351.0NaN